Dual-process theories or recognition posit that participants can recognize a stimulus as having been studied earlier because 1) the stimulus seems familiar, or 2) they recollect specific details pertaining to that stimulus; recent neuropsychological evidence suggests that familiarity and recollection are subserved by distinct brain structures (rhinal neocortex and the hippocampus, respectively). The goal of the proposed research is to: 1) use neural network models to explain how neocortex implements familiarity, and how the hippocampus implements recollection; and 2) test these models predictions regarding recognition performance in normal subjects and subjects with focal hippocampal damage. The first specific aim is to establish, using simulations and experiments, key qualitative differences between neocortical and hippocampal contributions to recognition (e.g., I will explore the idea that increasing the similarity of lures to studied items impairs neocortically-driven recognition performance more that hippocampally-driven recognition performance). The second specific aim is to integrate the neocortical and hippocampal models, and use the combined model to: 1) precisely account for recognition data when both processes are contributing to recognition; and 2) explore the relationship between familiarity and recollection (e.g., are they independent). Extant formal models of recognition do not make contact with the underlying neurobiology as such, the proposed research constitutes a major step forward in recognition memory modeling. More practically, this research will improve our understanding of preserved memory capacities in brain-damaged patients; this, in turn, should benefit rehabilitation of these patients.